Biology subjects

Dhakal, K.

Publications and source records attributed to Dhakal, K..

3 recordsLinked to original sources

bioRxiv2021

RhizoVision Explorer: Open-source software for root image analysis and measurement standardization

Roots are central to the function of natural and agricultural ecosystems by driving plant acquisition of soil resources and influencing the carbon cycle. Root characteristics like length, diameter, and volume are critical to measure to understand plant and soil functions. RhizoVision Explorer is an open-source software designed to enable researchers interested in roots by providing an easy-to-use interface, fast image processing, and reliable measurements. The default broken roots mode is intended for roots sampled from pots or soil cores, washed, and typically scanned on a flatbed scanner, and provides measurements like length, diameter, and volume. The optional whole root mode for complete root systems or root crowns provides additional measurements such as angles, root depth, and convex hull. Both modes support providing measurements grouped by defined diameter ranges, the inclusion of multiple regions of interest, and batch analysis. RhizoVision Explorer was successfully validated against ground truth data using a novel copper wire image set. In comparison, the current reference software, the commercial WinRhizo, drastically underestimated volume when wires of different diameters were in the same image. Additionally, measurements were compared with WinRhizo and IJ_Rhizo using a simulated root image set, showing general agreement in software measurements, except for root volume. Finally, scanned root image sets acquired in different labs for the crop, herbaceous, and tree species were used to compare results from RhizoVision Explorer with WinRhizo. The two software showed general agreement, except that WinRhizo substantially underestimated root volume relative to RhizoVision Explorer. In the current context of rapidly growing interest in root science, RhizoVision Explorer intends to become a reference software, improve the overall accuracy and replicability of root trait measurements, and provide a foundation for collaborative improvement and reliable access to all. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

plant biology↗

bioRxiv2021

Interactions among rooting traits for deep water and nitrogen uptake in upland and lowland ecotypes of switchgrass (Panicum virgatum L.)

Plant phenotypic plasticity in response to nutrient and water availability is an important adaptation for abiotic stress tolerance. Roots intercept water and nutrients while foraging through soil searching for further resources. Substantial amounts of nitrate can leach into groundwater; yet, little is known about how deep rooting affects this process. Here, we phenotyped root system traits and deep 15N nitrate capture across 1.5 m profiles of solid-media using tall mesocosms in switchgrass (Panicum virgatum L.), a cellulosic bioenergy feedstock. Root and shoot biomass, photosynthesis and respiration, and nutrient uptake traits were quantified in response to a water and nitrate stress factorial experiment in the greenhouse for switchgrass upland (VS16) and lowland (AP13) ecotypes. The two switchgrass ecotypes shared common plastic abiotic responses to nitrogen (N) and water availability and yet showed genotypic differences for root and shoot traits. A significant interaction between nitrogen and water stress for axial and lateral root traits represents a complex and shared root development strategy for stress mitigation. Deep root growth and 15N capture were found to be closely linked to aboveground growth. Together, these results represent the wide genetic pool of switchgrass and that deep rooting promotes nitrate capture, plant productivity, and sustainability. HighlightTwo main ecotypes of switchgrass have both shared and different root responses to varying water and nitrogen conditions, with deep rooting shown to be closely linked to aboveground growth.

plant biology↗

bioRxiv2020

Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture

O_LIThe root economics space is a useful framework for plant ecology, but rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. C_LIO_LIWe phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO2 flux and the open-source software RhizoVision Explorer for analyzing scanned images. C_LIO_LIWe uncovered substantial variation for specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and construction costs. Multiple linear regression estimated that lateral root tips had the greatest SRR, and the residuals of this model were used as a new trait. SRR was negatively correlated with plant mass. Network analysis using a Gaussian graphical model identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with aspects of the root economics space, with underlying gene candidates. C_LIO_LICombining functional phenomics and root economics is a promising approach to understand crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems. C_LI

plant biology↗